{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src='http://www.ic.uff.br/images/identidade_visual/Logo-Instituto-de-Computacao.png' width='20%' align='left'>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "# `nsgaiii`: Understanding NSGA-III with a Python Implementation\n",
    "\n",
    "## [Luis Martí](http://lmarti.com)\n",
    "\n",
    "### [Institute of Computing](http://www.ic.uff.br), [Universidade Federal Fluminense](http://www.uff.br)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "In this notebook we will explore NSGA-III and introduce its implementation in Python, that is distributed as the [`nsgaiii` module](http://nsgaiii.github.com)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preparing the environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import time, array, random, copy, math\n",
    "from itertools import chain\n",
    "from operator import attrgetter, itemgetter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "button": false,
    "collapsed": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import mpl_toolkits.mplot3d as a3\n",
    "from matplotlib.path import Path\n",
    "import matplotlib.patches as patches\n",
    "\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In case you want to run this notebook on your own you need IPython and the [DEAP evolutionary computation module](https://www.github.com/DEAP/deap) with version 1.1.0 or above (at the time of writing this version is only available by cloning it from the GitHub repository)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "button": false,
    "collapsed": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "from deap import algorithms, base, benchmarks, tools, creator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from nsgaiii import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Version of the modules used. Go to https://github.com/jrjohansson/version_information to install extension. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/json": {
       "Software versions": [
        {
         "module": "Python",
         "version": "3.5.1 64bit [GCC 4.2.1 (Apple Inc. build 5577)]"
        },
        {
         "module": "IPython",
         "version": "4.0.1"
        },
        {
         "module": "OS",
         "version": "Darwin 15.2.0 x86_64 i386 64bit"
        },
        {
         "module": "numpy",
         "version": "1.10.2"
        },
        {
         "module": "matplotlib",
         "version": "1.5.1"
        },
        {
         "module": "deap",
         "version": "1.1"
        },
        {
         "module": "nsgaiii",
         "version": "0.1.0"
        }
       ]
      },
      "text/html": [
       "<table><tr><th>Software</th><th>Version</th></tr><tr><td>Python</td><td>3.5.1 64bit [GCC 4.2.1 (Apple Inc. build 5577)]</td></tr><tr><td>IPython</td><td>4.0.1</td></tr><tr><td>OS</td><td>Darwin 15.2.0 x86_64 i386 64bit</td></tr><tr><td>numpy</td><td>1.10.2</td></tr><tr><td>matplotlib</td><td>1.5.1</td></tr><tr><td>deap</td><td>1.1</td></tr><tr><td>nsgaiii</td><td>0.1.0</td></tr><tr><td colspan='2'>Wed Jan 20 15:53:03 2016 CET</td></tr></table>"
      ],
      "text/latex": [
       "\\begin{tabular}{|l|l|}\\hline\n",
       "{\\bf Software} & {\\bf Version} \\\\ \\hline\\hline\n",
       "Python & 3.5.1 64bit [GCC 4.2.1 (Apple Inc. build 5577)] \\\\ \\hline\n",
       "IPython & 4.0.1 \\\\ \\hline\n",
       "OS & Darwin 15.2.0 x86\\_64 i386 64bit \\\\ \\hline\n",
       "numpy & 1.10.2 \\\\ \\hline\n",
       "matplotlib & 1.5.1 \\\\ \\hline\n",
       "deap & 1.1 \\\\ \\hline\n",
       "nsgaiii & 0.1.0 \\\\ \\hline\n",
       "\\hline \\multicolumn{2}{|l|}{Wed Jan 20 15:53:03 2016 CET} \\\\ \\hline\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "Software versions\n",
       "Python 3.5.1 64bit [GCC 4.2.1 (Apple Inc. build 5577)]\n",
       "IPython 4.0.1\n",
       "OS Darwin 15.2.0 x86_64 i386 64bit\n",
       "numpy 1.10.2\n",
       "matplotlib 1.5.1\n",
       "deap 1.1\n",
       "nsgaiii 0.1.0\n",
       "Wed Jan 20 15:53:03 2016 CET"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%load_ext version_information \n",
    "%version_information numpy, matplotlib, deap, nsgaiii"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `nsgaiii` source code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by loading and inspecting the source code of the module. As we want to play with we will load all the supporting methods that otherwise would remain hidden after the `import` statement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# %load nsgaiii/selection.py\n",
    "#    This file is part of nsgaiii, a Python implementation of NSGA-III.\n",
    "#\n",
    "#    nsgaiii is free software: you can redistribute it and/or modify\n",
    "#    it under the terms of the GNU Lesser General Public License as\n",
    "#    published by the Free Software Foundation, either version 3 of\n",
    "#    the License, or (at your option) any later version.\n",
    "#\n",
    "#    nsgaiii is distributed in the hope that it will be useful,\n",
    "#    but WITHOUT ANY WARRANTY; without even the implied warranty of\n",
    "#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n",
    "#    GNU Lesser General Public License for more details.\n",
    "#\n",
    "#    You should have received a copy of the GNU Lesser General Public\n",
    "#    License along with nsgaiii. If not, see <http://www.gnu.org/licenses/>.\n",
    "#\n",
    "#    by Luis Marti (IC/UFF) http://lmarti.com\n",
    "\n",
    "import copy,random\n",
    "import numpy as np\n",
    "from deap import tools\n",
    "\n",
    "class ReferencePoint(list):\n",
    "    '''A reference point exists in objective space an has a set of individuals\n",
    "    associated to it.'''\n",
    "    def __init__(self, *args):\n",
    "        list.__init__(self, *args)\n",
    "        self.associations_count = 0\n",
    "        self.associations = []\n",
    "\n",
    "def generate_reference_points(num_objs, num_divisions_per_obj=4):\n",
    "    '''Generates reference points for NSGA-III selection. This code is based on\n",
    "    `jMetal NSGA-III implementation <https://github.com/jMetal/jMetal>`_.\n",
    "    '''\n",
    "    def gen_refs_recursive(work_point, num_objs, left, total, depth):\n",
    "        if depth == num_objs - 1:\n",
    "            work_point[depth] = left/total\n",
    "            ref = ReferencePoint(copy.deepcopy(work_point))\n",
    "            return [ref]\n",
    "        else:\n",
    "            res = []\n",
    "            for i in range(left):\n",
    "                work_point[depth] = i/total\n",
    "                res = res + gen_refs_recursive(work_point, num_objs, left-i, total, depth+1)\n",
    "            return res\n",
    "    return gen_refs_recursive([0]*num_objs, num_objs, num_objs*num_divisions_per_obj,\n",
    "                              num_objs*num_divisions_per_obj, 0)\n",
    "\n",
    "def find_ideal_point(individuals):\n",
    "    'Finds the ideal point from a set individuals.'\n",
    "    current_ideal = [np.infty] * len(individuals[0].fitness.values)\n",
    "    for ind in individuals:\n",
    "        # Use wvalues to accomodate for maximization and minimization problems.\n",
    "        current_ideal = np.minimum(current_ideal, \n",
    "                                  np.multiply(ind.fitness.wvalues, -1))\n",
    "    return current_ideal\n",
    "\n",
    "def find_extreme_points(individuals):\n",
    "    'Finds the individuals with extreme values for each objective function.'\n",
    "    return [sorted(individuals, key=lambda ind:ind.fitness.wvalues[o] * -1)[-1]\n",
    "            for o in range(len(individuals[0].fitness.values))]\n",
    "\n",
    "def construct_hyperplane(individuals, extreme_points):\n",
    "    'Calculates the axis intersects for a set of individuals and its extremes.'\n",
    "    def has_duplicate_individuals(individuals):\n",
    "        for i in range(len(individuals)):\n",
    "            for j in range(i+1, len(individuals)):\n",
    "                if individuals[i].fitness.values == individuals[j].fitness.values:\n",
    "                    return True\n",
    "        return False\n",
    "\n",
    "    num_objs = len(individuals[0].fitness.values)\n",
    "\n",
    "    if has_duplicate_individuals(extreme_points):\n",
    "        intercepts = [extreme_points[m].fitness.values[m] for m in range(num_objs)]\n",
    "    else:\n",
    "        b = np.ones(num_objs)\n",
    "        A = [point.fitness.values for point in extreme_points]\n",
    "        x = np.linalg.solve(A,b)\n",
    "        intercepts = 1/x\n",
    "    return intercepts\n",
    "\n",
    "def normalize_objective(individual, m, intercepts, ideal_point, epsilon=1e-20):\n",
    "    'Normalizes an objective.'\n",
    "    # Numeric trick present in JMetal implementation.\n",
    "    if np.abs(intercepts[m]-ideal_point[m] > epsilon):\n",
    "        return individual.fitness.values[m] / (intercepts[m]-ideal_point[m])\n",
    "    else:\n",
    "        return individual.fitness.values[m] / epsilon\n",
    "\n",
    "def normalize_objectives(individuals, intercepts, ideal_point):\n",
    "    '''Normalizes individuals using the hyperplane defined by the intercepts as\n",
    "    reference. Corresponds to Algorithm 2 of Deb & Jain (2014).'''\n",
    "    num_objs = len(individuals[0].fitness.values)\n",
    "\n",
    "    for ind in individuals:\n",
    "        ind.fitness.normalized_values = list([normalize_objective(ind, m,\n",
    "                                                                  intercepts, ideal_point)\n",
    "                                                                  for m in range(num_objs)])\n",
    "    return individuals\n",
    "\n",
    "def perpendicular_distance(direction, point):\n",
    "    k = np.dot(direction, point) / np.sum(np.power(direction, 2))\n",
    "    d = np.sum(np.power(np.subtract(np.multiply(direction, [k] * len(direction)), point) , 2))\n",
    "    return np.sqrt(d)\n",
    "\n",
    "def associate(individuals, reference_points):\n",
    "    '''Associates individuals to reference points and calculates niche number.\n",
    "    Corresponds to Algorithm 3 of Deb & Jain (2014).'''\n",
    "    pareto_fronts = tools.sortLogNondominated(individuals, len(individuals))\n",
    "    num_objs = len(individuals[0].fitness.values)\n",
    "\n",
    "    for ind in individuals:\n",
    "        rp_dists = [(rp, perpendicular_distance(ind.fitness.normalized_values, rp))\n",
    "                    for rp in reference_points]\n",
    "        best_rp, best_dist = sorted(rp_dists, key=lambda rpd:rpd[1])[0]\n",
    "        ind.reference_point = best_rp\n",
    "        ind.ref_point_distance = best_dist\n",
    "        best_rp.associations_count +=1 # update de niche number\n",
    "        best_rp.associations += [ind]\n",
    "\n",
    "def niching_select(individuals, k):\n",
    "    '''Secondary niched selection based on reference points. Corresponds to\n",
    "    steps 13-17 of Algorithm 1 and to Algorithm 4.'''\n",
    "    if len(individuals) == k:\n",
    "        return individuals\n",
    "\n",
    "    #individuals = copy.deepcopy(individuals)\n",
    "\n",
    "    ideal_point = find_ideal_point(individuals)\n",
    "    extremes = find_extreme_points(individuals)\n",
    "    intercepts = construct_hyperplane(individuals, extremes)\n",
    "    normalize_objectives(individuals, intercepts, ideal_point)\n",
    "\n",
    "    reference_points = generate_reference_points(len(individuals[0].fitness.values))\n",
    "\n",
    "    associate(individuals, reference_points)\n",
    "\n",
    "    res = []\n",
    "    while len(res) < k:\n",
    "        min_assoc_rp = min(reference_points, key=lambda rp: rp.associations_count)\n",
    "        min_assoc_rps = [rp for rp in reference_points if rp.associations_count == min_assoc_rp.associations_count]\n",
    "        chosen_rp = min_assoc_rps[random.randint(0, len(min_assoc_rps)-1)]\n",
    "\n",
    "        #print('Rps',min_assoc_rp.associations_count, chosen_rp.associations_count, len(min_assoc_rps))\n",
    "\n",
    "        associated_inds = chosen_rp.associations\n",
    "\n",
    "        if chosen_rp.associations:\n",
    "            if chosen_rp.associations_count == 0:\n",
    "                sel = min(chosen_rp.associations, key=lambda ind: ind.ref_point_distance)\n",
    "            else:\n",
    "                sel = chosen_rp.associations[random.randint(0, len(chosen_rp.associations)-1)]\n",
    "            res += [sel]\n",
    "            chosen_rp.associations.remove(sel)\n",
    "            chosen_rp.associations_count += 1\n",
    "            individuals.remove(sel)\n",
    "        else:\n",
    "            reference_points.remove(chosen_rp)\n",
    "    return res\n",
    "\n",
    "def sel_nsga_iii(individuals, k):\n",
    "    '''Implements NSGA-III selection as described in\n",
    "    Deb, K., & Jain, H. (2014). An Evolutionary Many-Objective Optimization\n",
    "    Algorithm Using Reference-Point-Based Nondominated Sorting Approach,\n",
    "    Part I: Solving Problems With BoxConstraints. IEEE Transactions on\n",
    "    Evolutionary Computation, 18(4), 577–601. doi:10.1109/TEVC.2013.2281535.\n",
    "    '''\n",
    "    assert len(individuals) >= k\n",
    "\n",
    "    if len(individuals)==k:\n",
    "        return individuals\n",
    "\n",
    "    # Algorithm 1 steps 4--8\n",
    "    fronts = tools.sortLogNondominated(individuals, len(individuals))\n",
    "\n",
    "    limit = 0\n",
    "    res =[]\n",
    "    for f, front in enumerate(fronts):\n",
    "        res += front\n",
    "        if len(res) > k:\n",
    "            limit = f\n",
    "            break\n",
    "    # Algorithm 1 steps\n",
    "    selection = []\n",
    "    if limit > 0:\n",
    "        for f in range(limit):\n",
    "            selection += fronts[f]\n",
    "\n",
    "    # complete selected inividuals using the referece point based approach\n",
    "    selection += niching_select(fronts[limit], k - len(selection))\n",
    "    return selection\n",
    "\n",
    "__all__ = [\"sel_nsga_iii\"]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Understanding NSGA-III selection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to understand the NSGA-III selection mechanism we will make an example iteration of solving a three-objectives DTLZ2 problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "button": false,
    "collapsed": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "creator.create(\"FitnessMin3\", base.Fitness, weights=(-1.0,) * 3)\n",
    "creator.create(\"Individual3\", array.array, typecode='d', \n",
    "               fitness=creator.FitnessMin3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "The `toolbox` contains the configuration of the algorithm:\n",
    "\n",
    "* how to create an individual,\n",
    "* how to create a population,\n",
    "* the evolutionary operators,\n",
    "* the evaluation function, and\n",
    "* the selection method.\n",
    "\n",
    "The `prepare_toolbox()` function encapsulates the configuration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "button": false,
    "collapsed": true,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "def prepare_toolbox(problem_instance, selection_func, number_of_variables, bounds_low, bounds_up):\n",
    "    \n",
    "    def uniform(low, up, size=None):\n",
    "        try:\n",
    "            return [random.uniform(a, b) for a, b in zip(low, up)]\n",
    "        except TypeError:\n",
    "            return [random.uniform(a, b) for a, b in zip([low] * size, [up] * size)]\n",
    "    \n",
    "    toolbox = base.Toolbox()\n",
    "    \n",
    "    toolbox.register('evaluate', problem_instance)\n",
    "    toolbox.register('select', selection_func)\n",
    "    \n",
    "    toolbox.register(\"attr_float\", uniform, bounds_low, bounds_up, number_of_variables)\n",
    "    toolbox.register(\"individual\", tools.initIterate, creator.Individual3, toolbox.attr_float)\n",
    "    toolbox.register(\"population\", tools.initRepeat, list, toolbox.individual)\n",
    "    \n",
    "    toolbox.register(\"mate\", tools.cxSimulatedBinaryBounded, \n",
    "                     low=bounds_low, up=bounds_up, eta=20.0)\n",
    "    toolbox.register(\"mutate\", tools.mutPolynomialBounded, \n",
    "                     low=bounds_low, up=bounds_up, eta=20.0, \n",
    "                     indpb=1.0/number_of_variables)\n",
    "\n",
    "    toolbox.pop_size = 100   # population size\n",
    "    toolbox.max_gen = 200    # max number of iteration\n",
    "    toolbox.mut_prob = 1/number_of_variables\n",
    "    toolbox.cross_prob = 0.3\n",
    "    \n",
    "    return toolbox"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preparing an instance of `toolbox`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "button": false,
    "collapsed": true,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "number_of_variables = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "button": false,
    "collapsed": true,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "bounds_low, bounds_up = 0, 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "toolbox = prepare_toolbox(lambda ind: benchmarks.dtlz2(ind, 3), \n",
    "                          sel_nsga_iii, number_of_variables,\n",
    "                          bounds_low, bounds_up)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing refence point selection\n",
    "\n",
    "Creating a population and evaluating it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pop = toolbox.population(n=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for ind in pop:\n",
    "    ind.fitness.values = toolbox.evaluate(ind)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "button": false,
    "collapsed": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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Z/e7v/q5+67d+S+973/uKPpyJoyYB5kaQVuVvxvI3a6rvCxTvC+Rv1mTdSNWr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rWL58OR577DF885vfxKJFiyp9eBKfIITg4sWLGB4eNkwQz507BwBYtWqV0Wqxr68Pt956a1lM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\nGLy8vKo902+xWHTmzBl99dVXeuihhxQRESGbzaaTJ08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      "text/plain": [
       "<matplotlib.figure.Figure at 0x108566518>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 516,
       "width": 516
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9,9))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "# the coordinate origin (black + sign)\n",
    "ax.scatter(0,0,0, c='k', marker='+', s=100)\n",
    "\n",
    "# the population (purple)\n",
    "for ind in pop:\n",
    "    ax.scatter(ind.fitness.values[0],\n",
    "               ind.fitness.values[1], \n",
    "               ind.fitness.values[2], \n",
    "               color='purple', c='mediumpurple',\n",
    "               s=30, marker='o')\n",
    "\n",
    "# ideal point (red star)\n",
    "ideal_point = find_ideal_point(pop)\n",
    "ax.scatter(ideal_point[0], ideal_point[1], ideal_point[2],\n",
    "           s=50, marker='*', color='salmon', c='red')\n",
    "\n",
    "# extreme points marked (red)\n",
    "extremes = find_extreme_points(pop)\n",
    "for i,ex in enumerate(extremes):\n",
    "    ax.scatter(ex.fitness.values[0],\n",
    "               ex.fitness.values[1], \n",
    "               ex.fitness.values[2], s=30, c='r', marker='o', color='r')\n",
    "\n",
    "# intercepts (in green)\n",
    "intercepts = construct_hyperplane(pop, extremes)\n",
    "verts = [(intercepts[0], 0, 0), (0, intercepts[1], 0), (0, 0, intercepts[2])]\n",
    "\n",
    "for vert in verts:\n",
    "    ax.scatter(vert[0], vert[1], vert[2], c='lightgreen', color='forestgreen', s=100, marker='.')\n",
    "    \n",
    "tri = a3.art3d.Poly3DCollection([verts])\n",
    "tri.set_color('lightgreen')\n",
    "tri.set_alpha(0.11)\n",
    "tri.set_edgecolor('lightgreen')\n",
    "ax.add_collection3d(tri)\n",
    "\n",
    "# normalized objectives (light blue)\n",
    "normalize_objectives(pop, intercepts, ideal_point)\n",
    "\n",
    "for ind in pop:\n",
    "    ax.scatter(ind.fitness.normalized_values[0], \n",
    "               ind.fitness.normalized_values[1], \n",
    "               ind.fitness.normalized_values[2], color='navy', marker='o', c='lightblue')\n",
    "\n",
    "# reference points (gray)\n",
    "rps = generate_reference_points(3)\n",
    "for rp in rps:\n",
    "    ax.scatter(rp[0], rp[1], rp[2], marker='o', c='lightgray', color='gray')\n",
    "\n",
    "# final figure details   \n",
    "ax.set_xlabel('$f_1()$', fontsize=15)\n",
    "ax.set_ylabel('$f_2()$', fontsize=15)\n",
    "ax.set_zlabel('$f_3()$', fontsize=15)\n",
    "ax.view_init(elev=9, azim=-40)\n",
    "plt.autoscale(tight=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Associating individuals to reference points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "associate(pop, rps)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resulting associations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NO3Yc1IoV29XTc6K5QV+frQ0bmtXQ0Kpt25Zr6dLy1G0w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\niIiIiMzK/we317h0cB8SmgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108a80b70>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 404,
       "width": 404
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(7,7))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "# the coordinate origin\n",
    "ax.scatter(0,0,0, c='k', marker='+', s=100)\n",
    "\n",
    "for rp in rps:\n",
    "    ax.scatter(rp[0], rp[1], rp[2], marker='o', c='lightgray', color='gray')\n",
    "\n",
    "pairs = []\n",
    "for ind in pop:\n",
    "    ax.scatter(ind.fitness.normalized_values[0], \n",
    "               ind.fitness.normalized_values[1], \n",
    "               ind.fitness.normalized_values[2], color='navy', marker='o', c='lightblue')\n",
    "    pairs += [(ind.fitness.normalized_values, ind.reference_point)]\n",
    "\n",
    "lin = a3.art3d.Line3DCollection(pairs)\n",
    "lin.set_color('blue')\n",
    "ax.add_collection3d(lin)\n",
    "\n",
    "# final figure details   \n",
    "ax.set_xlabel('$f_1()$', fontsize=15)\n",
    "ax.set_ylabel('$f_2()$', fontsize=15)\n",
    "ax.set_zlabel('$f_3()$', fontsize=15)\n",
    "ax.view_init(elev=11, azim=-21)\n",
    "plt.autoscale(tight=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Implementing NSGA-III"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Having the selection mechanism the implementantion of NSGA-III is very simple thanks to DEAP."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def nsga_iii(toolbox, stats=None, verbose=False):\n",
    "    population = toolbox.population(n=toolbox.pop_size)\n",
    "    return algorithms.eaMuPlusLambda(population, toolbox,\n",
    "                              mu=toolbox.pop_size, \n",
    "                              lambda_=toolbox.pop_size, \n",
    "                              cxpb=toolbox.cross_prob, \n",
    "                              mutpb=toolbox.mut_prob,\n",
    "                              ngen=toolbox.max_gen,\n",
    "                              stats=stats, verbose=verbose)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We create a `Statistics` instance to store the populations in every iteration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "button": false,
    "collapsed": true,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "stats = tools.Statistics()\n",
    "stats.register('pop', copy.deepcopy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Running NSGA-III..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 7min 16s, sys: 10.2 s, total: 7min 26s\n",
      "Wall time: 8min 1s\n"
     ]
    }
   ],
   "source": [
    "%time res, logbook = nsga_iii(toolbox, stats=stats)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resulting population."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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GI0RGv69yBnvZOi1KUniVfaUjFnE/kYv79kc/F6Y4OpPJhCGlUqlUTeFxHIfiaLRkaeF9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zUJhUJIJBJoaGiA2+2u9uaUHb3iIRQKQZIkZRZc67160qwKCQ2rPXgLpVmxwVixogOoPTerfKhT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\nkQIAAADAKH8D4fzIEOzzDSYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a928278>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 404,
       "width": 404
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(7,7))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "for ind in res:\n",
    "    ax.scatter(ind.fitness.values[0],\n",
    "               ind.fitness.values[1],\n",
    "               ind.fitness.values[2], c='purple', marker='o', color='mediumpurple')\n",
    "\n",
    "ax.set_xlabel('$f_1()$', fontsize=15)\n",
    "ax.set_ylabel('$f_2()$', fontsize=15)\n",
    "ax.set_zlabel('$f_3()$', fontsize=15)\n",
    "ax.view_init(elev=11, azim=-21)\n",
    "plt.autoscale(tight=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting hypervolume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pops = logbook.select('pop')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from deap.tools._hypervolume import hv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def hypervolume(individuals, ref=None):\n",
    "    front = tools.sortLogNondominated(individuals, len(individuals), first_front_only=True)\n",
    "    wobjs = np.array([ind.fitness.wvalues for ind in front]) * -1\n",
    "    if ref is None:\n",
    "        ref = np.max(wobjs, axis=0) + 1\n",
    "    return hv.hypervolume(wobjs, ref)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pops_obj = [np.array([ind.fitness.wvalues for ind in pop]) * -1 for pop in pops]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ref = np.max([np.max(wobjs, axis=0) for wobjs in pops_obj], axis=0) + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "hypervols = [hypervolume(pop, ref) for pop in pops]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10acba6a0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3XZxojBlTNQrMXXfFqDB9+0pvvplqEQEkrKIiLiBMmiR98EG0cR8zJkZV2nHH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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a2b76a0>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 270,
       "width": 396
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(hypervols)\n",
    "plt.xlabel('Iterations (t)')\n",
    "plt.ylabel('Hypervolume')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The End"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "@font-face {\n",
       "    font-family: 'Optima';\n",
       "    src: url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.eot?raw=true');\n",
       "    src: url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.eot?raw=true?#iefix') format('embedded-opentype'),\n",
       "         url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.woff?raw=true') format('woff'),\n",
       "         url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.ttf?raw=true') format('truetype');\n",
       "    font-weight: normal;\n",
       "    font-style: normal;\n",
       "\n",
       "}\n",
       ".text_cell_render h1 {\n",
       "    font-family: 'Optima', sans-serif;\n",
       "    font-style:regular;\n",
       "    font-weight: 200;\n",
       "    text-align: left;\n",
       "    /*font-size: 300%;*/\n",
       "    line-height: 100%;\n",
       "    color:#000000;\n",
       "    margin-bottom: 0.1em;\n",
       "    margin-top: 0.5em;\n",
       "    display: block;\n",
       "}\n",
       "\n",
       "div.text_cell_render{\n",
       "    font-family: 'Optima', sans-serif;\n",
       "    line-height: 120%;\n",
       "    font-size: 110%;\n",
       "    font-weight: 400;\n",
       "    text-align: justify;\n",
       "    margin-left:0em;\n",
       "    margin-right:0em;\n",
       "}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ignore this cell... contains only the visual tunning of the notebook.\n",
    "from IPython.core.display import HTML\n",
    "HTML(\"\"\"\n",
    "<style>\n",
    "@font-face {\n",
    "    font-family: 'Optima';\n",
    "    src: url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.eot?raw=true');\n",
    "    src: url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.eot?raw=true?#iefix') format('embedded-opentype'),\n",
    "         url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.woff?raw=true') format('woff'),\n",
    "         url('https://github.com/functional-koans/clojure-koans-web/blob/master/public/stylesheets/optima-webfont.ttf?raw=true') format('truetype');\n",
    "    font-weight: normal;\n",
    "    font-style: normal;\n",
    "\n",
    "}\n",
    ".text_cell_render h1 {\n",
    "    font-family: 'Optima', sans-serif;\n",
    "    font-style:regular;\n",
    "    font-weight: 200;\n",
    "    text-align: left;\n",
    "    /*font-size: 300%;*/\n",
    "    line-height: 100%;\n",
    "    color:#000000;\n",
    "    margin-bottom: 0.1em;\n",
    "    margin-top: 0.5em;\n",
    "    display: block;\n",
    "}\n",
    "\n",
    "div.text_cell_render{\n",
    "    font-family: 'Optima', sans-serif;\n",
    "    line-height: 120%;\n",
    "    font-size: 110%;\n",
    "    font-weight: 400;\n",
    "    text-align: justify;\n",
    "    margin-left:0em;\n",
    "    margin-right:0em;\n",
    "}\n",
    "</style>\n",
    "\"\"\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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